FM / retribert

/usr/local/lib/python3.6/site-packages/transformers/models/retribert/

/usr/local/lib/python3.6/site-packages/transformers/models/retribert

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_retribert.py	5151	0644	edit dl rm
modeling_retribert.py	9261	0644	edit dl rm
tokenization_retribert.py	1823	0644	edit dl rm
tokenization_retribert_fast.py	2203	0644	edit dl rm
__init__.py	1993	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/retribert/tokenization_retribert.py (1823B)

# coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tokenization classes for RetriBERT."""

from ...utils import logging
from ..bert.tokenization_bert import BertTokenizer

logger = logging.get_logger(__name__)

VOCAB_FILES_NAMES = {"vocab_file": "vocab.txt"}

PRETRAINED_VOCAB_FILES_MAP = {
    "vocab_file": {
        "yjernite/retribert-base-uncased": "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt",
    }
}

PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
    "yjernite/retribert-base-uncased": 512,
}

PRETRAINED_INIT_CONFIGURATION = {
    "yjernite/retribert-base-uncased": {"do_lower_case": True},
}

class RetriBertTokenizer(BertTokenizer):
    r"""
    Constructs a RetriBERT tokenizer.

[`RetroBertTokenizer`] is identical to [`BertTokenizer`] and runs end-to-end tokenization: punctuation splitting
    and wordpiece.

Refer to superclass [`BertTokenizer`] for usage examples and documentation concerning parameters.
    """

vocab_files_names = VOCAB_FILES_NAMES
    pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
    max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    pretrained_init_configuration = PRETRAINED_INIT_CONFIGURATION
    model_input_names = ["input_ids", "attention_mask"]

cmd: